Hacker News Reader

Comment by abcd_f | Hacker News Reader

> User-Extensible Rank Polymorphism

> IMO this is what makes something an array language.

Great to hear. So what is it?

Not op, but I assume it means that there's rank polymorphism (i.e. data can be of arbitrary dimensions, and there's support for things like functions working on both N-dimensions, without having to specify n, or maybe setting constraints on n), and that the polymorphism can be used on the programmer side (so it's not limited to just a handful of language builtins) through the oop equivalent of subclasses and interfaces.

A question, would you interpret this as rank polymorphism?

  schema do
    input do
      array :regions do
        float :tax_rate
        array :offices do
          float :col_adjustment
          array :employees do
            float :salary
            float :rating
          end
        end
      end
    end

    trait :high_performer, input.regions.offices.employees.rating > 4.5
    
    value :bonus do
      on high_performer, input.regions.offices.employees.salary * 0.25
      base input.regions.offices.employees.salary * 0.10
    end
    
    value :final_pay,
      (input.regions.offices.employees.salary + bonus * input.regions.offices.col_adjustment) *
      (1 - input.regions.tax_rate)
  end

  result = schema.from(nested_data)[:final_pay]
  # => [[[91_000, 63_700], [58_500]], [[71_225]]]

I think i'm misunderstanding, rank is explicit throughout this example but i'm not familiar with this syntax (ruby maybe?) but whatever the case i don't see the rank polymorphism.

If i'm reading the syntax correctly, this would translate in kdb/q to a raze (flatten) on the 3 dimensions (regions, offices, employees). Probably more likely to be expressed as a converge but in either case, the calculations here are not possible in a rank polymorphic way.

The broadcasting handles the rank differences automatically. When bonus (at employee level) multiplies with col_adjustment (at office level), each employee's bonus gets their office's adjustment applied, no flattening or manual reshaping. The structure [[[91_000, 63_700], [58_500]], [[71_225]]] was preserved.

This is from a Ruby DSL I'm working on (Kumi). Probably the broadcasting semantics are very different from traditional rank operators in q/APL?

Edit: I realized that I missed the input structure:

  Region 0: Office 0 has 2 employees, Office 1 has 1 employee
  Region 1: Office 0 has 1 employee

Just had a quick browse of the kumi readme - very cool, i like it

That means a lot, thanks!

I didn't downvote but was utterly puzzled with your example. After your response below, it occurs to me that you are confusing Employee rank (a business concept) with Array rank a mathematical concept. Either that or it is very strange explanation for rank polymorphism.

The programmer can define functions that operate on matrices without having to be explicit about the number of dimensions and possibly (types of data, size of data, or length).

Example 1: A function that can take as input a 4x2x8 matrix or a 3x7 matrix.

Example 2: A function that can take as input a 4x2x8 matrix and a 3x7 matrix and output a third matrix.

> A function that can take as input a 4x2x8 matrix and a 3x7 matrix and output a third matrix.

which shows that this feature request is complete jibberish

Why gibberish ? It's a common feature in both array languages and Iverson ghosts, and many find it extremely useful.

You mean like a "winner" function able to check for both Tic-Tac-Toe, a Connect Four field and a Similar 3D+ tower game?

I'm not sure I follow? The "winning" condition is different in all of those examples?

X adjacent cell values in an N dimensional array? For tic tac toe, it's 3 in a row, for connect 4 it's 4 in a row.

Fair enough, I guess. The "available moves" would be dramatically different, such that I'm not clear I see much of a win on this reuse. But, yeah, fair enough.

It was just the simplest case I could think of that would be reasonable. I'm not a heavy enough pure math guy to really get how an Array centric language is even all that valuable myself TBF.

Rank polymorphism means that a function can be polymorphic in the additional dimensions of arrays. For example, if you write a function that takes a 2x3 and a 4x5 array, it can also work on 10x15x2x3 and 10x15x4x5 arrays by broadcasting.

If rank polymorphism results in accepting both 4x2x8 and 3x7, then that means the function was a function on elements to begin with. Which is possible, but not the most interesting application of rank polymorphism.

> Rank polymorphism means that a function can be polymorphic in the additional dimensions of arrays. For example, if you write a function that takes a 2x3 and a 4x5 array, it can also work on 10x15x2x3 and 10x15x4x5 arrays by broadcasting.

Thanks, this is what I was ineloquently attempting to describe with "A function that can take as input a 4x2x8 matrix or a 3x7 matrix."

game math libraries often have this (and glsl gpu shader language), like "2 * vec3(1,2,3)" results in "vec3(2,4,6)"

There are other cases like adding vectors to matrices and so on, but in the end this logic is defined in some custom add operator overload on a class or object in the language.

(I had no idea what it meant either until i searched for examples..)

I wondered the same. Similarly I wish the author had provided examples for statements like

> Numpy also needs to be paired with a JIT compiler to make python a real array language

Reply on news.ycombinator.com